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1. Assume that the...

1. Assume that the data has a normal distribution and the number of observations is greater than fifty. Find the critical z value used to test a null hypothesis. ALPHA = 0.05 for a left-tailed test.

-1.96

±1.96

±1.645

-1.645

2. Find the value of the test statistic z using z = W4T2 The claim is that the proportion of accidental deaths of the elderly attributable to residential falls is more than 0.10, and the sample statistics include n = 800 deaths of the elderly with 15% of them attributable to residential falls.

3.96

-3.96

4.71

-4.71

3. Use the given information to find the P-value. Also, use a 0.05 significance level and state the conclusion about the null hypothesis (reject the null hypothesis or fail to reject the null hypothesis). The test statistic in a right-tailed test is z = 1.43.

0.1528; fail to reject the null hypothesis

0.1528; reject the null hypothesis

0.0764; fail to reject the null hypothesis

0.0764; reject the null hypothesis

4. Find the number of successes x suggested by the given statement. Among 720 people selected randomly from among the residents of one city, 13.89% were found to be living below the official poverty line.

100

101

104

99

5. Assume that you plan to use a significance level of alpha = 0.05 to test the claim that p1 = p2. Use the given sample sizes and numbers of successes to find the z test statistic for the hypothesis test. A random sampling of sixty pitchers from the National League and fifty-two pitchers from the American League showed that 19 National and 11 American League pitchers had E.R.A's below 3.5.

z = 1.629

z = 1.253

z = 191.183

z = 15.457

6. Assume that you plan to use a significance level of alpha = 0.05 to test the claim that p1 = p2. Use the given sample sizes and numbers of successes to find the P-value for the hypothesis test. n1 = 50; n2 = 50x1 = 8; x2 = 7

0.3897

0.6103

0.7794

0.2206

7. Construct the indicated confidence interval for the difference between population proportions . Assume that the samples are independent and that they have been randomly selected. In a random sample of 300 women, 49% favored stricter gun control legislation. In a random sample of 200 men, 28% favored stricter gun control legislation. Construct a 98% confidence interval for the difference between the population proportions p1 - p2.

0.126 < p1 - p2 < 0.294

0.110 < p1 - p2 < 0.310

0.122 < p1 - p2 < 0.298

0.099 < p1 - p2 < 0.321

8. Construct the indicated confidence interval for the difference between the two population means. Assume that the two samples are independent simple random samples selected from normally distributed populations. Also assume that the population standard deviations are equal (sigma1 = sigma2), so that the standard error of the difference between means is obtained by pooling the sample variances.A researcher was interested in comparing the resting pulse rates of people who exercise regularly and people who do not exercise regularly. Independent simple random samples were obtained of 16 people who do not exercise regularly and 12 people who do exercise regularly. The resting pulse rate (in beats per minute) of each person was recorded. The summary statistics are as follows.W4T8Construct a 90% confidence interval for the difference between the mean pulse rate of people who do not exercise regularly and the mean pulse rate of people who exercise regularly.

-0.34 beats/min < mu1 - mu2 < 7.74 beats/min

-1.13 beats/min < mu1 - mu2 < 8.53 beats/min

-3.22 beats/min < mu1 - mu2 < 10.62 beats/min

-2.57 beats/min < mu1 - mu2 < 9.97 beats/min

9. The two data sets are dependent. Find d-bar to the nearest tenth.W4T9

-0.8

-0.6

-0.7

-0.4

10. Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r = 0.843, n = 5

Critical values: r = ±0.878, significant linear correlation

Critical values: r = ±0.950, no significant linear correlation

Critical values: r = 0.950, significant linear correlation

Critical values: r = ±0.878, no significant linear correlation

-1.96

±1.96

±1.645

-1.645

2. Find the value of the test statistic z using z = W4T2 The claim is that the proportion of accidental deaths of the elderly attributable to residential falls is more than 0.10, and the sample statistics include n = 800 deaths of the elderly with 15% of them attributable to residential falls.

3.96

-3.96

4.71

-4.71

3. Use the given information to find the P-value. Also, use a 0.05 significance level and state the conclusion about the null hypothesis (reject the null hypothesis or fail to reject the null hypothesis). The test statistic in a right-tailed test is z = 1.43.

0.1528; fail to reject the null hypothesis

0.1528; reject the null hypothesis

0.0764; fail to reject the null hypothesis

0.0764; reject the null hypothesis

4. Find the number of successes x suggested by the given statement. Among 720 people selected randomly from among the residents of one city, 13.89% were found to be living below the official poverty line.

100

101

104

99

5. Assume that you plan to use a significance level of alpha = 0.05 to test the claim that p1 = p2. Use the given sample sizes and numbers of successes to find the z test statistic for the hypothesis test. A random sampling of sixty pitchers from the National League and fifty-two pitchers from the American League showed that 19 National and 11 American League pitchers had E.R.A's below 3.5.

z = 1.629

z = 1.253

z = 191.183

z = 15.457

6. Assume that you plan to use a significance level of alpha = 0.05 to test the claim that p1 = p2. Use the given sample sizes and numbers of successes to find the P-value for the hypothesis test. n1 = 50; n2 = 50x1 = 8; x2 = 7

0.3897

0.6103

0.7794

0.2206

7. Construct the indicated confidence interval for the difference between population proportions . Assume that the samples are independent and that they have been randomly selected. In a random sample of 300 women, 49% favored stricter gun control legislation. In a random sample of 200 men, 28% favored stricter gun control legislation. Construct a 98% confidence interval for the difference between the population proportions p1 - p2.

0.126 < p1 - p2 < 0.294

0.110 < p1 - p2 < 0.310

0.122 < p1 - p2 < 0.298

0.099 < p1 - p2 < 0.321

8. Construct the indicated confidence interval for the difference between the two population means. Assume that the two samples are independent simple random samples selected from normally distributed populations. Also assume that the population standard deviations are equal (sigma1 = sigma2), so that the standard error of the difference between means is obtained by pooling the sample variances.A researcher was interested in comparing the resting pulse rates of people who exercise regularly and people who do not exercise regularly. Independent simple random samples were obtained of 16 people who do not exercise regularly and 12 people who do exercise regularly. The resting pulse rate (in beats per minute) of each person was recorded. The summary statistics are as follows.W4T8Construct a 90% confidence interval for the difference between the mean pulse rate of people who do not exercise regularly and the mean pulse rate of people who exercise regularly.

-0.34 beats/min < mu1 - mu2 < 7.74 beats/min

-1.13 beats/min < mu1 - mu2 < 8.53 beats/min

-3.22 beats/min < mu1 - mu2 < 10.62 beats/min

-2.57 beats/min < mu1 - mu2 < 9.97 beats/min

9. The two data sets are dependent. Find d-bar to the nearest tenth.W4T9

-0.8

-0.6

-0.7

-0.4

10. Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r = 0.843, n = 5

Critical values: r = ±0.878, significant linear correlation

Critical values: r = ±0.950, no significant linear correlation

Critical values: r = 0.950, significant linear correlation

Critical values: r = ±0.878, no significant linear correlation

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